Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Discounted cash flow analysis for real estate: Identifying best practice: A dissertation submitted in partial fulfilment of the requirements for the degree of Master of Property Studies at Lincoln University

The Valuation of institutional grade real estate using discounted cash flow analysis has become increasing popular during the past fifteen years. The sophistication has increased, aided by computer technology and the development of spreadsheet applications. The sophistication of discounted cash flow models, which derive exact conclusions, can give a perception of precision which is unwarranted. The concern is that the precision is only implied. This research identifies the three key components of the discounted cash flow framework, which drive the conclusions, and uses four resource areas to determine how best these key components can be derived for maximum conclusion reliability and supportability

Climatologic studies inside Sandy Glacier at Mount Hood Volcano in Oregon, USA

Previous investigations of climatic conditions of glaciers primarily focused on the glacier’s surface or on the moulin as the entrance to the glacier’s interior. Many glaciers, however, contain far-reaching cave systems inside the ice that have been understood and investigated as drainage systems for meltwater. Until now, there have been no comprehensive climate studies inside a glacier cave. Thus, the climatic conditions, as well as their effects on the glacier, are unknown. The first climatologic investigations inside the cave system of Sandy Glacier on Mt. Hood in Oregon (USA) in June 2015 have shown that both thermic activity of the volcanic subsurface and chimney effects between the glacier snout at the base of the glacier and higher opening of the moulin can cause drastic melting inside the glacier. Those processes lead to considerably stronger melting from the inside than observations at the surface suggest and can cause an unexpected collapse over a distance of several hundred meters. We will present and assess the first measuring results of both the thermic and flow conditions inside Sandy Glacier

Climatologic studies inside Sandy Glacier at Mount Hood Volcano in Oregon, USA

Previous investigations of climatic conditions of glaciers primarily focused on the glacier’s surface or on the moulin as the entrance to the glacier’s interior. Many glaciers, however, contain far-reaching cave systems inside the ice that have been understood and investigated as drainage systems for meltwater. Until now, there have been no comprehensive climate studies inside a glacier cave. Thus, the climatic conditions, as well as their effects on the glacier, are unknown. The first climatologic investigations inside the cave system of Sandy Glacier on Mt. Hood in Oregon (USA) in June 2015 have shown that both thermic activity of the volcanic subsurface and chimney effects between the glacier snout at the base of the glacier and higher opening of the moulin can cause drastic melting inside the glacier. Those processes lead to considerably stronger melting from the inside than observations at the surface suggest and can cause an unexpected collapse over a distance of several hundred meters. We will present and assess the first measuring results of both the thermic and flow conditions inside Sandy Glacier

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease